Abstract

Artificial fish swarm algorithm is a technique based on swarm behaviors that are inspired from schooling behaviors of fishes swarm in the nature. Group escaping is another interesting behavior of fish that is ignored. This behavior shows all fish change their moving directions rapidly while some fish sense a predator. In this paper, we proposed a new algorithm which is obtained by hybridizing artificial fish swarm algorithm and group escaping behavior of fish which can greatly speed up the convergence. It is presented proper pseudocode of improved algorithm and then experimental results on Traveling Salesman Problem is applied and demonstrated the advantages of the improved algorithm.